A unified conceptual framework for metabolic phenotyping in diagnosis and prognosis

Everett, J.R., Holmes, E., Veselkov, K.A., Lindon, J.C. and Nicholson, J.K. (2019) A unified conceptual framework for metabolic phenotyping in diagnosis and prognosis. Trends in Pharmacological Sciences, 40 (10). pp. 763-773.

Abstract

Understanding metabotype (multicomponent metabolic characteristics) variation can help to generate new diagnostic and prognostic biomarkers, as well as models, with potential to impact on patient management. We present a suite of conceptual approaches for the generation, analysis, and understanding of metabotypes from body fluids and tissues. We describe and exemplify four fundamental approaches to the generation and utilization of metabotype data via multiparametric measurement of (i) metabolite levels, (ii) metabolic trajectories, (iii) metabolic entropies, and (iv) metabolic networks and correlations in space and time. This conceptual framework can underpin metabotyping in the scenario of personalized medicine, with the aim of improving clinical outcomes for patients, but the framework will have value and utility in areas of metabolic profiling well beyond this exemplar.

Item Type:	Journal Article
Murdoch Affiliation(s):	Australian National Phenome Center
Publisher:	Elsevier (Cell Press)
Copyright:	© 2019 Elsevier Ltd.
URI:	http://researchrepository.murdoch.edu.au/id/eprint/52544

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